Long-term outcomes of mesial temporal laser interstitial thermal therapy for drug-resistant epilepsy and subsequent surgery for seizure recurrence: a multi-centre cohort study.

BACKGROUND: Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) is a minimally invasive alternative to surgical resection for drug-resistant mesial temporal lobe epilepsy (mTLE). Reported rates of seizure freedom are variable and long-term durability is largely unproven. Anterior temporal lobectomy (ATL) remains an option for patients with MRgLITT treatment failure. However, the safety and efficacy of this staged strategy is unknown. METHODS: This multicentre, retrospective cohort study included 268 patients consecutively treated with mesial temporal MRgLITT at 11 centres between 2012 and 2018. Seizure outcomes and complications of MRgLITT and any subsequent surgery are reported. Predictive value of preoperative variables for seizure outcome was assessed. RESULTS: Engel I seizure freedom was achieved in 55.8% (149/267) at 1 year, 52.5% (126/240) at 2 years and 49.3% (132/268) at the last follow-up ≥1 year (median 47 months). Engel I or II outcomes were achieved in 74.2% (198/267) at 1 year, 75.0% (180/240) at 2 years and 66.0% (177/268) at the last follow-up. Preoperative focal to bilateral tonic-clonic seizures were independently associated with seizure recurrence. Among patients with seizure recurrence, 14/21 (66.7%) became seizure-free after subsequent ATL and 5/10 (50%) after repeat MRgLITT at last follow-up≥1 year. CONCLUSIONS: MRgLITT is a viable treatment with durable outcomes for patients with drug-resistant mTLE evaluated at a comprehensive epilepsy centre. Although seizure freedom rates were lower than reported with ATL, this series represents the early experience of each centre and a heterogeneous cohort. ATL remains a safe and effective treatment for well-selected patients who fail MRgLITT.

Source-sink connectivity: a novel interictal EEG marker for seizure localization.

Over 15 million epilepsy patients worldwide have drug-resistant epilepsy. Successful surgery is a standard of care treatment but can only be achieved through complete resection or disconnection of the epileptogenic zone, the brain region(s) where seizures originate. Surgical success rates vary between 20% and 80%, because no clinically validated biological markers of the epileptogenic zone exist. Localizing the epileptogenic zone is a costly and time-consuming process, which often requires days to weeks of intracranial EEG (iEEG) monitoring. Clinicians visually inspect iEEG data to identify abnormal activity on individual channels occurring immediately before seizures or spikes that occur interictally (i.e. between seizures). In the end, the clinical standard mainly relies on a small proportion of the iEEG data captured to assist in epileptogenic zone localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored interictal data to better diagnose and treat patients. IEEG offers a unique opportunity to observe epileptic cortical network dynamics but waiting for seizures increases patient risks associated with invasive monitoring. In this study, we aimed to leverage interictal iEEG data by developing a new network-based interictal iEEG marker of the epileptogenic zone. We hypothesized that when a patient is not clinically seizing, it is because the epileptogenic zone is inhibited by other regions. We developed an algorithm that identifies two groups of nodes from the interictal iEEG network: those that are continuously inhibiting a set of neighbouring nodes ('sources') and the inhibited nodes themselves ('sinks'). Specifically, patient-specific dynamical network models were estimated from minutes of iEEG and their connectivity properties revealed top sources and sinks in the network, with each node being quantified by source-sink metrics. We validated the algorithm in a retrospective analysis of 65 patients. The source-sink metrics identified epileptogenic regions with 73% accuracy and clinicians agreed with the algorithm in 93% of seizure-free patients. The algorithm was further validated by using the metrics of the annotated epileptogenic zone to predict surgical outcomes. The source-sink metrics predicted outcomes with an accuracy of 79% compared to an accuracy of 43% for clinicians' predictions (surgical success rate of this dataset). In failed outcomes, we identified brain regions with high metrics that were untreated. When compared with high frequency oscillations, the most commonly proposed interictal iEEG feature for epileptogenic zone localization, source-sink metrics outperformed in predictive power (by a factor of 1.2), suggesting they may be an interictal iEEG fingerprint of the epileptogenic zone.

Long-term seizure and psychiatric outcomes following laser ablation of mesial temporal structures.

OBJECTIVE: Postsurgical seizure outcome following laser interstitial thermal therapy (LiTT) for the management of drug-resistant mesial temporal lobe epilepsy (MTLE) has been limited to 2 years. Furthermore, its impact on presurgical mood and anxiety disorders has not been investigated. The objectives of this study were (1) to identify seizure outcome changes over a period ranging from 18 to 81 months; (2) to investigate the seizure-free rate in the last follow-up year; (3) to identify the variables associated with seizure freedom; and (4) to identify the impact of LiTT on presurgical mood and anxiety disorders. METHODS: Medical records of all patients who underwent LiTT for MTLE from 2013 to 2019 at the University of Miami Comprehensive Epilepsy Center were retrospectively reviewed. Demographic, epilepsy-related, cognitive, psychiatric, and LiTT-related data were compared between seizure-free (Engel Class I) and non-seizure-free (Engel Class II + III + IV) patients. Statistical analyses included univariate and multivariate stepwise logistic regression analyses. RESULTS: Forty-eight patients (mean age = 43 ± 14.2 years, range = 21-78) were followed for a mean period of 50 ± 20.7 months (range = 18-81); 29 (60.4%) achieved an Engel Class I outcome, whereas 11 (22.9%) had one to three seizures/year. Seizure-freedom rate decreased from 77.8% to 50% among patients with 24- and >61-month follow-up periods, respectively. In the last follow-up year, 83% of all patients were seizure-free. Seizure freedom was associated with having mesial temporal sclerosis (MTS), no presurgical focal to bilateral tonic-clonic seizures, and no psychopathology in the last follow-up year. Presurgical mood and/or anxiety disorder were identified in 30 patients (62.5%) and remitted after LiTT in 19 (62%). SIGNIFICANCE: LiTT appears to be a safe and effective surgical option for treatment-resistant MTLE, particularly among patients with MTS. Remission of presurgical mood and anxiety disorders can also result from LiTT.

Machine learning to predict passenger mortality and hospital length of stay following motor vehicle collision.

OBJECTIVE: Motor vehicle collisions (MVCs) account for 1.35 million deaths and cost $518 billion US dollars each year worldwide, disproportionately affecting young patients and low-income nations. The ability to successfully anticipate clinical outcomes will help physicians form effective management strategies and counsel families with greater accuracy. The authors aimed to train several classifiers, including a neural network model, to accurately predict MVC outcomes. METHODS: A prospectively maintained database at a single institution's level I trauma center was queried to identify all patients involved in MVCs over a 20-year period, generating a final study sample of 16,287 patients from 1998 to 2017. Patients were categorized by in-hospital mortality (during admission) and length of stay (LOS), if admitted. All models included age (years), Glasgow Coma Scale (GCS) score, and Injury Severity Score (ISS). The in-hospital mortality and hospital LOS models further included time to admission. RESULTS: After comparing a variety of machine learning classifiers, a neural network most effectively predicted the target features. In isolated testing phases, the neural network models returned reliable, highly accurate predictions: the in-hospital mortality model performed with 92% sensitivity, 90% specificity, and a 0.98 area under the receiver operating characteristic curve (AUROC), and the LOS model performed with 2.23 days mean absolute error after optimization. CONCLUSIONS: The neural network models in this study predicted mortality and hospital LOS with high accuracy from the relatively few clinical variables available in real time. Multicenter prospective validation is ultimately required to assess the generalizability of these findings. These next steps are currently in preparation.

Design-development of an at-home modular brain-computer interface (BCI) platform in a case study of cervical spinal cord injury.

OBJECTIVE: The objective of this study was to develop a portable and modular brain-computer interface (BCI) software platform independent of input and output devices. We implemented this platform in a case study of a subject with cervical spinal cord injury (C5 ASIA A). BACKGROUND: BCIs can restore independence for individuals with paralysis by using brain signals to control prosthetics or trigger functional electrical stimulation. Though several studies have successfully implemented this technology in the laboratory and the home, portability, device configuration, and caregiver setup remain challenges that limit deployment to the home environment. Portability is essential for transitioning BCI from the laboratory to the home. METHODS: The BCI platform implementation consisted of an Activa PC + S generator with two subdural four-contact electrodes implanted over the dominant left hand-arm region of the sensorimotor cortex, a minicomputer fixed to the back of the subject's wheelchair, a custom mobile phone application, and a mechanical glove as the end effector. To quantify the performance for this at-home implementation of the BCI, we quantified system setup time at home, chronic (14-month) decoding accuracy, hardware and software profiling, and Bluetooth communication latency between the App and the minicomputer. We created a dataset of motor-imagery labeled signals to train a binary motor imagery classifier on a remote computer for online, at-home use. RESULTS: Average bluetooth data transmission delay between the minicomputer and mobile App was 23 ± 0.014 ms. The average setup time for the subject's caregiver was 5.6 ± 0.83 min. The average times to acquire and decode neural signals and to send those decoded signals to the end-effector were respectively 404.1 ms and 1.02 ms. The 14-month median accuracy of the trained motor imagery classifier was 87.5 ± 4.71% without retraining. CONCLUSIONS: The study presents the feasibility of an at-home BCI system that subjects can seamlessly operate using a friendly mobile user interface, which does not require daily calibration nor the presence of a technical person for at-home setup. The study also describes the portability of the BCI system and the ability to plug-and-play multiple end effectors, providing the end-user the flexibility to choose the end effector to accomplish specific motor tasks for daily needs. Trial registration ClinicalTrials.gov: NCT02564419. First posted on 9/30/2015.

Effects of an external ventricular drain alert protocol on venticulostomy placement time in the emergency department.

OBJECTIVE: Timely ventriculostomy placement is critical in the management of neurosurgical emergencies. Prompt external ventricular drain (EVD) placement has been shown to improve long-term patient outcomes and decrease the length of ICU and hospital stays. Successful and efficient EVD placement requires seamless coordination among multiple healthcare teams. In this study, the authors sought to identify factors favoring delayed ventriculostomy via a quality improvement initiative and to implement changes to expedite EVD placement. METHODS: Through process mapping, root cause analysis, and interviews with staff, the authors identified the lack of a standardized mechanism for alerting necessary healthcare teams as a major contributor to delays in EVD placement. In December 2019, an EVD alert system was developed to automatically initiate an EVD placement protocol and to alert the neurosurgery department, pharmacy, core laboratory, and nursing staff to prepare for EVD placement. The time to EVD placement was tracked prospectively using time stamps in the electronic medical record. RESULTS: A total of 20 patients who underwent EVD placement between December 2019 and April 2021, during the EVD alert protocol initiation, and 18 preprotocol control patients (January 2018 to December 2019) met study inclusion criteria and were included in the analysis. The mean time to EVD placement in the control group was 71.88 minutes compared with 50.3 minutes in the EVD alert group (two-tailed t-test, p = 0.025). The median time to EVD placement was 64 minutes in the control group compared with 52 minutes in the EVD alert group (rank-sum test, p = 0.0184). All patients from each cohort exhibited behavior typical of stable processes, with no violation of Shewhart rules and no special cause variations on statistical process control charts. CONCLUSIONS: A quality improvement framework helped identify sources of delays to EVD placement in the emergency department. An automated EVD alert system was a simple intervention that significantly reduced the time to EVD placement in the emergency department and can be easily implemented at other institutions to improve patient care.

Freezing of Gait in Parkinson's Disease: Invasive and Noninvasive Neuromodulation.

INTRODUCTION: Freezing of gait (FoG) is one of the most disabling yet poorly understood symptoms of Parkinson's disease (PD). FoG is an episodic gait pattern characterized by the inability to step that occurs on initiation or turning while walking, particularly with perception of tight surroundings. This phenomenon impairs balance, increases falls, and reduces the quality of life. MATERIALS AND METHODS: Clinical-anatomical correlations, electrophysiology, and functional imaging have generated several mechanistic hypotheses, ranging from the most distal (abnormal central pattern generators of the spinal cord) to the most proximal (frontal executive dysfunction). Here, we review the neuroanatomy and pathophysiology of gait initiation in the context of FoG, and we discuss targets of central nervous system neuromodulation and their outcomes so far. The PubMed database was searched using these key words: neuromodulation, freezing of gait, Parkinson's disease, and gait disorders. CONCLUSION: Despite these investigations, the pathogenesis of this process remains poorly understood. The evidence presented in this review suggests FoG to be a heterogenous phenomenon without a single unifying pathologic target. Future studies rigorously assessing targets as well as multimodal approaches will be essential to define the next generation of therapeutic treatments.

Effects of surgical targeting in laser interstitial thermal therapy for mesial temporal lobe epilepsy: A multicenter study of 234 patients.

OBJECTIVE: Laser interstitial thermal therapy (LITT) for mesial temporal lobe epilepsy (mTLE) has reported seizure freedom rates between 36% and 78% with at least 1 year of follow-up. Unfortunately, the lack of robust methods capable of incorporating the inherent variability of patient anatomy, the variability of the ablated volumes, and clinical outcomes have limited three-dimensional quantitative analysis of surgical targeting and its impact on seizure outcomes. We therefore aimed to leverage a novel image-based methodology for normalizing surgical therapies across a large multicenter cohort to quantify the effects of surgical targeting on seizure outcomes in LITT for mTLE. METHODS: This multicenter, retrospective cohort study included 234 patients from 11 centers who underwent LITT for mTLE. To investigate therapy location, all ablation cavities were manually traced on postoperative magnetic resonance imaging (MRI), which were subsequently nonlinearly normalized to a common atlas space. The association of clinical variables and ablation location to seizure outcome was calculated using multivariate regression and Bayesian models, respectively. RESULTS: Ablations including more anterior, medial, and inferior temporal lobe structures, which involved greater amygdalar volume, were more likely to be associated with Engel class I outcomes. At both 1 and 2 years after LITT, 58.0% achieved Engel I outcomes. A history of bilateral tonic-clonic seizures decreased chances of Engel I outcome. Radiographic hippocampal sclerosis was not associated with seizure outcome. SIGNIFICANCE: LITT is a viable treatment for mTLE in patients who have been properly evaluated at a comprehensive epilepsy center. Consideration of surgical factors is imperative to the complete assessment of LITT. Based on our model, ablations must prioritize the amygdala and also include the hippocampal head, parahippocampal gyrus, and rhinal cortices to maximize chances of seizure freedom. Extending the ablation posteriorly has diminishing returns. Further work is necessary to refine this analysis and define the minimal zone of ablation necessary for seizure control.

Analysis of intra-operative variables as predictors of 30-day readmission in patients undergoing glioma surgery at a single center.

PURPOSE: Reducing the time from surgery to adjuvant chemoradiation, by decreasing unnecessary readmissions, is paramount for patients undergoing glioma surgery. The effects of intraoperative risk factors on 30-day readmission rates for such patients is currently unclear. We utilized a predictive model-driven approach to assess the impact of intraoperative factors on 30-day readmission rates for the cranial glioma patient. METHODS: Retrospectively, the intraoperative records of 290 patients who underwent glioma surgery at a single institution by a single surgeon were assessed. Data on operative variables including anesthesia specific factors were analyzed via univariate and stepwise regression analysis for impact on 30-day readmission rates. A predictive model was built to assess the capability of these results to predict readmission and validated using leave-one-out cross-validation. RESULTS: In multivariate analysis, end case hypothermia (OR 0.28, 95% CI [0.09, 0.84]), hypertensive time > 15 min (OR 2.85, 95% CI [1.21, 6.75]), and pre-operative Karnofsky performance status (KPS) (OR 0.63, 95% CI [0.41, 0.98] were identified as being significantly associated with 30-day readmission rates (chi-squared statistic vs. constant model 25.2, p < 0.001). Cross validation of the model resulted in an overall accuracy of 89.7%, a specificity of 99.6%, and area under the receiver operator curve (AUC) of 0.763. CONCLUSION: Intraoperative risk factors may help risk-stratify patients with a high degree of accuracy and improve postoperative patient follow-up. Attention should be paid to duration of hypertension and end-case final temperature as these represent potentially modifiable factors that appear to be highly associated with 30-day readmission rates. Prospective validation of our model is needed to assess its potential for implementation as a screening tool to identify patients undergoing glioma surgery who are at a higher risk of post-operative readmission within 30 days.

Predictive modeling of brain tumor laser ablation dynamics.

INTRODUCTION: Laser interstitial thermal therapy (LITT) is a novel MR thermometry-guided thermoablative tool revolutionizing the clinical management of brain tumors. A limitation of LITT is our inability to estimate a priori how tissues will respond to thermal energy, which hinders treatment planning and delivery. The aim of this study was to determine whether brain tumor LITT ablation dynamics may be predicted by features of the preoperative MRI and the relevance of these data, if any, to the recurrence of metastases after LITT. METHODS: Intraoperative thermal damage estimate (TDE) map pixels representative of irreversible damage were retrospectively quantified relative to ablation onset for 101 LITT procedures. Raw TDE pixel counts and TDE pixel counts modelled with first order dynamics were related to eleven independent variables derived from the preoperative MRI, demographics, laser settings, and tumor pathology. Stepwise regression analysis generated predictive models of LITT dynamics, and leave-one-out cross validation evaluated the accuracy of these models at predicting TDE pixel counts solely from the independent variables. Using a deformable atlas, TDE maps were co-registered to the immediate post-ablation MRI, allowing comparison of predicted and actual ablation sizes. RESULTS: Brain tumor TDE pixel counts modelled with first order dynamics, but not raw pixel counts, are correlated with the independent variables. Independent variables showing strong relations to the TDE pixel measures include T1 gadolinium and T2 signal, perfusion, and laser power. Associations with tissue histopathology are minimal. Leave-one-out analysis demonstrates that predictive models using these independent variables account for 77% of the variance observed in TDE pixel counts. Analysis of metastases treated revealed a trend towards the over-estimation of LITT effects by TDE maps during rapid ablations, which was associated with tumor recurrence. CONCLUSIONS: Features of the preoperative MRI are predictive of LITT ablation dynamics and could eventually be used to improve the clinical efficacy with which LITT is delivered to brain tumors.

Clinically Significant Visual Deficits after Laser Interstitial Thermal Therapy for Mesiotemporal Epilepsy.

BACKGROUND: Laser interstitial thermal therapy (LITT) has recently gained popularity as a minimally invasive surgical option for the treatment of mesiotemporal epilepsy (mTLE). Similar to traditional open procedures for epilepsy, the most frequent neurological complications of LITT are visual deficits; however, a critical analysis of these injuries is lacking. OBJECTIVES: To evaluate the visual deficits that occur after LITT for mTLE and their etiology. METHOD: We surveyed five academic epilepsy centers that regularly perform LITT for cases of self-reported postoperative visual deficits. For these patients all pre-, intra- and postoperative MRIs were co-registered with an anatomic atlas derived from 7T MRI data. This was used to estimate thermal injury to early visual pathways and measure imaging variables relevant to the LITT procedure. Using logistic regression, we then compared 14 variables derived from demographics, mesiotemporal anatomy, and the surgical procedure for the patients with visual deficits to a normal cohort comprised of the first 30 patients to undergo this procedure at a single institution. RESULTS: Of 90 patients that underwent LITT for mTLE, 6 (6.7%) reported a postoperative visual deficit. These included 2 homonymous hemianopsias (HHs), 2 quadrantanopsias, and 2 cranial nerve (CN) IV palsies. These deficits localized to the posterior aspect of the ablation, corresponding to the hippocampal body and tail, and tended to have greater laser energy delivered in that region than the normal cohort. The patients with HH had insult localized to the lateral geniculate nucleus, which was -associated with young age and low choroidal fissure CSF volume. Quadrantanopsia, likely from injury to the optic radiation in Meyer's loop, was correlated with a lateral trajectory and excessive energy delivered at the tail end of the ablation. Patients with CN IV injury had extension of contrast to the tentorial edge associated with a mesial laser trajectory. CONCLUSIONS: LITT for epilepsy may be complicated by various classes of visual deficit, each with distinct etiology and clinical significance. It is our hope that by better understanding these injuries and their mechanisms we can eventually reduce their occurrence by identifying at-risk patients and trajectories and appropriately tailoring the ablation procedure.

Gender Disparities in Deep Brain Stimulation for Parkinson's Disease.

OBJECTIVES: This study sought to determine whether there is a gender disparity in patients undergoing deep brain stimulation (DBS) surgery for Parkinson's disease (PD) at a single health system, and better understand the reasons for this discrepancy. MATERIALS AND METHODS: We analyzed data from the University of Miami DBS Database, which included 3251 PD patients, using chi-square, repeated measures ANOVA, and t tests to examine gender differences in the number of patients referred for surgery, reasons for referral, number receiving/not receiving surgery, reasons for not receiving surgery, and postsurgical outcomes. RESULTS: During the study period, 207 PD patients were referred for DBS (75.8% male), and 100 underwent surgery (77.0% male). Of those who did not receive surgery, the most common reasons were need for further medical optimization (26.2%), suboptimal performance on neuropsychological evaluation (22.4%), other reason (20.6%), lost to follow-up (18.7%), or patient preference (12.2%). However, in women one of the most common reasons was patient preference (28.0%), and this was significant compared to men (p < 0.001). Men were more likely to be lost to follow-up (p = 0.046). There was no statistically significant difference in postsurgical outcomes. CONCLUSIONS: Despite similar postsurgical improvements, women were less likely to undergo DBS surgery due to their own preference, while men were more likely to be lost to follow-up. These data underscore the need for increased education and awareness of DBS so that all patients with PD who qualify for surgery can benefit from this procedure.

Laser thermal ablation for mesiotemporal epilepsy: Analysis of ablation volumes and trajectories.

OBJECTIVE: To identify features of ablations and trajectories that correlate with optimal seizure control and minimize the risk of neurocognitive deficits in patients undergoing laser interstitial thermal therapy (LiTT) for mesiotemporal epilepsy (mTLE). METHODS: Clinical and radiographic data were reviewed from a prospectively maintained database of all patients undergoing LiTT for the treatment of mTLE at the University of Miami Hospital. Standard preoperative and postoperative evaluations, including contrast-enhanced magnetic resonance imaging (MRI) and neuropsychological testing, were performed in all patients. Laser trajectory and ablation volumes were computed both by manual tracing of mesiotemporal structures and by nonrigid registration of ablation cavities to a common reference system based on 7T MRI data. RESULTS: Among 23 patients with at least 1-year follow-up, 15 (65%) were free of disabling seizures since the time of their surgery. Sparing of the mesial hippocampal head was significantly correlated with persistent disabling seizures (p = 0.01). A lateral trajectory through the hippocampus showed a trend for poor seizure outcome (p = 0.08). A comparison of baseline and postoperative neurocognitive testing revealed areas of both improvement and worsening, which were not associated with ablation volume or trajectory. SIGNIFICANCE: At 1-year follow-up, LiTT appears to be a safe and effective tool for the treatment of mTLE, although a longer follow-up period is necessary to confirm these observations. Better understanding of the impact of ablation volume and location could potentially fine-tune this technique to improve seizure-freedom rates and associated neurologic and cognitive changes.

Validation of the International Classification of Diseases, Tenth Revision-Clinical Modification Diagnostic Code for Essential Tremor.

Background: The positive predictive value (PPV) of the International Classification of Diseases, Ninth Revision-Clinical Modification (ICD-9-CM) code for "essential and other specified forms of tremor" in identifying essential tremor (ET) cases was found to be less than 50%. The ability of the ICD-10-CM G25.0 code for "essential tremor" to identify ET has not been determined. The study objective was to determine the PPV of the G25.0 code. Methods: Patients in a tertiary health system with a primary care encounter associated with ICD-10-CM code G25.0 in 2022 underwent medical record review to determine if the consensus criteria from the International Parkinson and Movement Disorder Society for an ET diagnosis were met. Results: 442 patients were included. The PPV of G25.0 in identifying probable ET cases was 74.7% (95% confidence interval (CI) 70.4-78.5%). Among patients prescribed propranolol, the PPV improved to 87.8% (95% CI 78.0-93.6%). Discussion: Compared to the ICD-9-CM code 333.1, G25.0 is superior for identifying ET cases. A potential limitation of this study is that the consensus criteria applied relies on nonspecific physical exam findings which may lead to an overestimation of the PPV of G25.0. Highlights: The ICD-10-CM diagnosis code for essential tremor has not been previously validated. The objective of this study was to determine the PPV of the G25.0 code. The PPV in identifying essential tremor cases was 74.7%. The PPV improved among patients prescribed propranolol.

Reasons for Hospitalizations and Emergency Department Visits Among Patients with Essential Tremor.

Background: Prior studies suggest that patients with essential tremor (ET) have increased rates of healthcare utilization, but the reason for this increased use is unknown. The objective of this study was to evaluate the reasons for healthcare use among ET patients. Methods: This was a retrospective cross-sectional study of ET patients with an admission or emergency department (ED) visit at a tertiary health system from 2018-2023. Patients were matched on an encounter level with control patients based on propensity scores incorporating age, sex, race, and co-morbid conditions. The primary outcome was the odds of an encounter for each diagnostic category comparing ET patients with matched controls. Results: Only inpatient admissions for neurologic diagnoses were more likely for ET compared to control patients (odds ratio (OR) 3.73, 95% confidence interval (CI) 2.54 - 5.49, p < 0.001). Once admissions related to the surgical treatment of tremor were excluded, admissions for neurologic diagnoses were equally likely among ET and control patients (OR 0.96, 95% CI 0.59 - 1.57, p = 0.88). Discussion: Surgical treatment of tremor appears to be a key driver of healthcare use among ET patients. Future investigations should examine the pattern of healthcare use of ET patients before and after surgery. Highlights: Prior studies have shown increased healthcare use among essential tremor (ET) patients. The objective of this study was to evaluate the reasons for healthcare use among ET patients compared to matched control patients. Surgical treatment of tremor was found to be a key driver of healthcare use among ET patients.

A surgical decision aid for occipital neuralgia with literature review and single center case series.

BACKGROUND: Occipital neuralgia (ON) is a debilitating headache disorder. Due to the rarity of this disorder and lack of high-level evidence, a clear framework for choosing the optimal surgical approach for medically refractory ON incorporating shared decision making with patients does not exist. METHODS: A literature review of studies reporting pain outcomes of patients who underwent surgical treatment for ON was performed, as well as a retrospective chart review of patients who underwent surgery for ON within our institution. RESULTS: Thirty-two articles met the inclusion criteria. A majority of the articles were retrospective case series (22/32). The mean number of patients across the studies was 34 (standard deviation (SD) 39). Among the 13 studies that reported change in pain score on 10-point scales, a study of 20 patients who had undergone C2 and/or C3 ganglionectomies reported the greatest reduction in pain intensity after surgery. The studies evaluating percutaneous ablative methods including radiofrequency ablation and cryoablation showed the smallest reduction in pain scores overall. At our institution from 2014 to 2023, 11 patients received surgical treatment for ON with a mean follow-up of 187 days (SD 426). CONCLUSION: Based on these results, the first decision aid for selecting a surgical approach to medically refractory ON is presented. The algorithm prioritizes nerve sparing followed by non-nerve sparing techniques with the incorporation of patient preference. Shared decision making is critical in the treatment of ON given the lack of clear scientific evidence regarding the superiority of a particular surgical method.

Stereoelectroencephalography Electrode Implantation for Inpatient Workup of Treatment-Resistant Depression.

BACKGROUND AND OBJECTIVES: Treatment-resistant depression is a leading cause of disability. Our center's trial for neurosurgical intervention for treatment-resistant depression involves a staged workup for implantation of a personalized, closed-loop neuromodulation device for refractory depression. The first stage ("stage 1") of workup involves implantation of 10 stereoelectroencephalography (SEEG) electrodes bilaterally into 5 anatomically defined brain regions and involves a specialized preoperative imaging and planning workup and a frame-based operating protocol. METHODS: We rely on diffusion tractography when planning stereotactic targets for 3 of 5 anatomic areas. We outline the rationale and fiber tracts that we focus on for targeting amygdala, ventral striatum and ventral capsule, and subgenual cingulate. We also outline frame-based stereotactic considerations for implantation of SEEG electrodes. EXPECTED OUTCOMES: Our method has allowed us to safely target all 5 brain areas in 3 of 3 trial participants in this ongoing study, with adequate fiber bundle contact in each of the 3 areas targeted using tractography. Furthermore, we ultimately used tractography data from our stage 1 workup to guide targeting near relevant fiber bundles for stage 2 (implantation of a responsive neuromodulation device). On completion of our data set, we will determine the overlap between volume of tissue activated for all electrodes and areas of interest defined by anatomy and tractography. DISCUSSION: Our protocol outlined for SEEG electrode implantation incorporates tractography and frame-based stereotaxy.

The sixth sense: how much does interictal intracranial EEG add to determining the focality of epileptic networks?

Intracranial EEG is used for two main purposes: to determine (i) if epileptic networks are amenable to focal treatment and (ii) where to intervene. Currently, these questions are answered qualitatively and differently across centres. There is a need to quantify the focality of epileptic networks systematically, which may guide surgical decision-making, enable large-scale data analysis and facilitate multi-centre prospective clinical trials. We analysed interictal data from 101 patients with drug-resistant epilepsy who underwent pre-surgical evaluation with intracranial EEG at a single centre. We chose interictal data because of its potential to reduce the morbidity and cost associated with ictal recording. Sixty-five patients had unifocal seizure onset on intracranial EEG, and 36 were non-focal or multi-focal. We quantified the spatial dispersion of implanted electrodes and interictal intracranial EEG abnormalities for each patient. We compared these measures against the '5 Sense Score,' a pre-implant prediction of the likelihood of focal seizure onset, assessed the ability to predict unifocal seizure onset by combining these metrics and evaluated how predicted focality relates to subsequent treatment and outcomes. The spatial dispersion of intracranial EEG electrodes predicted network focality with similar performance to the 5-SENSE score [area under the receiver operating characteristic curve = 0.68 (95% confidence interval 0.57, 0.78)], indicating that electrode placement accurately reflected pre-implant information. A cross-validated model combining the 5-SENSE score and the spatial dispersion of interictal intracranial EEG abnormalities significantly improved this prediction [area under the receiver operating characteristic curve = 0.79 (95% confidence interval 0.70, 0.88); P < 0.05]. Predictions from this combined model differed between surgical- from device-treated patients with an area under the receiver operating characteristic curve of 0.81 (95% confidence interval 0.68, 0.85) and between patients with good and poor post-surgical outcome at 2 years with an area under the receiver operating characteristic curve of 0.70 (95% confidence interval 0.56, 0.85). Spatial measures of interictal intracranial EEG abnormality significantly improved upon pre-implant predictions of network focality by area under the receiver operating characteristic curve and increased sensitivity in a single-centre study. Quantified focality predictions related to ultimate treatment strategy and surgical outcomes. While the 5-SENSE score weighed for specificity in their multi-centre validation to prevent unnecessary implantation, sensitivity improvement found in our single-centre study by including intracranial EEG may aid the decision on whom to perform the focal intervention. We present this study as an important step in building standardized, quantitative tools to guide epilepsy surgery.

Return of intracranial beta oscillations and traveling waves with recovery from traumatic brain injury.

Traumatic brain injury (TBI) remains a pervasive clinical problem associated with significant morbidity and mortality. However, TBI remains clinically and biophysically ill-defined, and prognosis remains difficult even with the standardization of clinical guidelines and advent of multimodality monitoring. Here we leverage a unique data set from TBI patients implanted with either intracranial strip electrodes during craniotomy or quad-lumen intracranial bolts with depth electrodes as part of routine clinical practice. By extracting spectral profiles of this data, we found that the presence of narrow-band oscillatory activity in the beta band (12-30 Hz) closely corresponds with the neurological exam as quantified with the standard Glasgow Coma Scale (GCS). Further, beta oscillations were distributed over the cortical surface as traveling waves, and the evolution of these waves corresponded to recovery from coma, consistent with the putative role of waves in perception and cognitive activity. We consequently propose that beta oscillations and traveling waves are potential biomarkers of recovery from TBI. In a broader sense, our findings suggest that emergence from coma results from recovery of thalamo-cortical interactions that coordinate cortical beta rhythms.